Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows tha...Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.展开更多
Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution ...Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution for removing bad data and getting clean ICESat data for land applications by using threshold values of reflectivity, saturation, and gain directly from ICESat＇s GLAS （Geoscience Laser Alteimeter System） 01, 05, and 06 products. It is found that each laser campaign needs different threshold compositions to assure qualified ICESat data and that bad data removal rates range from 9.6% （laser 2A） to 62.3% （laser 2B） for the test area in the Yili watershed, China. These thresholds would possibly be used in other regions to extract qualified ICESat footprints for land applications. However, it is recommended to use the steps proposed here to further examine the transferability of threshold values for other regions of different elevations and climate regimes. As an example, the resulting ICESat data are applied to examine lake level changes of two lakes in the study area.展开更多
基金supported by the China State Kay Basic Research Project(2013CBA01802)Chinese National Natural Science Foundation(41101337+2 种基金41001197and 31228021)the Fundamental Research Funds for the Central Universities(lzujbky-2013-103)
文摘Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.
基金We thank NASA＇s ICESat Science Project and the NSIDC for distribution of the ICESat data. This work was in part supported by the National Natural Science Foundation of China （Grant Nos. 41101337 and 31228021 ） and the Cultivation Fund of the Key Scientific and Technical Innovation Project, Ministry of Education of China （No. 708089）. Authors want to thank Donghui Yi （NASA/Goddard） for helpful discussion on the early stage of the study and Ning Lv （IGSNRR/CAS） for help in developing the IDL code when he was a visiting scholar at UTSA.
文摘Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution for removing bad data and getting clean ICESat data for land applications by using threshold values of reflectivity, saturation, and gain directly from ICESat＇s GLAS （Geoscience Laser Alteimeter System） 01, 05, and 06 products. It is found that each laser campaign needs different threshold compositions to assure qualified ICESat data and that bad data removal rates range from 9.6% （laser 2A） to 62.3% （laser 2B） for the test area in the Yili watershed, China. These thresholds would possibly be used in other regions to extract qualified ICESat footprints for land applications. However, it is recommended to use the steps proposed here to further examine the transferability of threshold values for other regions of different elevations and climate regimes. As an example, the resulting ICESat data are applied to examine lake level changes of two lakes in the study area.
